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        검색결과 1

        1.
        2018.05 구독 인증기관·개인회원 무료
        It has been recognized that the performance of pavements is closely related to the properties of the underlying unbound layers and subgrade. It has also been recognized that unbound pavement materials possess a complex nature and often exhibit nonlinear behaviors [1, 2]. The Mechanistic-Empirical Pavement Design Guide (MEPDG) is founded on the use of resilient modulus as the primary input parameter when characterizing unbound pavement materials [3, 4]. The resilient moduli of unbound materials are typically determined by performing repeated load triaxial (RLT) tests in the laboratory. Due to that laboratory resilient modulus tests require sophisticated equipment and trained operators following complicated test procedures, many transportation agencies may not have access to the laboratory facility and opt to correlate resilient modulus with field tests [5]. The long-term pavement performance (LTPP) program offers a large and diverse database that includes a range of laboratory-derived and field-derived properties for unbound materials of many in-service pavement sections. This study is aimed to utilize LTPP data to develop a correlation between the laboratory-derived resilient modulus and a field-derived parameter, dynamic cone penetration index (DCPI) for unbound aggregate materials. Data extracted from the LTPP database were subjected to a thorough quality check to ensure that the data are of good quality and without errors. One-on-one univariate regression was first performed to examine the significance of different variables, including DCPI and some physical properties such as dry unit weight, water content, plasticity index, percent passing No.200 sieve. The physical properties that show strong correlation were selected to be combined with field test parameter (DCPI) to conduct a multivariate regression analysis. A statistical model was developed for the prediction of resilient modulus of unbound aggregates from the DCP test parameters and physical properties. The model predicted a separate data set that did not participate in the correlation analysis, suggesting the success of applying the DCP test in evaluating the resilient modulus of pavement unbound aggregate materials.